code: def save_checkpoint(
      states, is_best, output_dir, filename="checkpoint.pth.tar"
  ):
      torch.save(states, os.path.join(output_dir, filename))
      if is_best:
          torch.save(
              states, os.path.join(output_dir, "model_best.pth.tar")
          )
  
imports: import os
  import torch
  import torch.optim
  import numpy
  from sklearn.metrics import auc
label_desc: Use image node_id 16 for calling a global function with example usage: save_checkpoint(states, is_best, output_dir, filename) without return types